An asynchronous transfer mode (ATM) network provides connection-oriented communication services with a guaranteed bandwidth. To carry data in the ATM network, a virtual circuit (VC) with a predetermined bandwidth is allocated. An adaptation layer of the network protocol keeps the VC open as long as the data rate matches the allocated bandwidth, see H. Saran, S. Keshav, “An empirical Evaluation of Virtual Circuit Holding Times in IP over ATM Networks,” Proc. of INFOCOM 1994, Y. Afek, M. Cohen, E. Haalman, Y. Mansour, “Dynamic Bandwidth Allocation Policies, ” 0743-166X/96 IEEE, and S. K. Biswas, R. Izmailov, “Design of a fair Bandwidth allocation Policy for VBR Traffic in ATM Networks,” IEEE/ACM Trans. On Networking, V:8, N:2, April 2000.
However, if the data rate changes, then the allocated bandwidth may need to be changed. Periodic rate adjustment methods measure and adjust the bandwidth at fixed time intervals, while adaptive methods attempt to adjust the bandwidth whenever a change is necessary. The adjustment can close the current VC and open a new one, or change the bandwidth allocation for the current VC.
Variable bit rate (VBR) data, e.g., compressed videos, pose a unique challenge because of rapid fluctuations in the bit rate. Specifically, for VBR video data, bandwidth requirements change due to unavoidable coding data structures. For example, MPEG uses B-frames, and group of pictures (GOP). Each GOP starts with an I-frame followed by a P-frame. B-frames have fewer bits than P- and I-frames. Motion activities also cause fluctuations in the bit rate because the number of bits in the P- and B-frames depend on the amount of motion in the video.
For VBR data, dynamic resource allocation is crucial, especially for traffic that is bursty in time scales from milliseconds to seconds or even minutes. This burstiness phenomenon at different time scales is called self-similarity. see M. W. Garrett, W. Willinger, “Analysis, Modeling, and Generation of Self-similar VBR Video Traffic,” ACM SIGCOMM, London, 1994. They found a relation between energy distribution of a signal in frequency domain and the level of traffic self-similarity. However, any analytical study that makes use of the link between self-similarity level and energy distribution to dynamically allocate network resources has not been done yet. It is known that increasing level of self-similarity of a traffic trace increases the required network resources to prevent QoS degradation, such as delay and packet loss rate. Therefore, a correct modeling and prediction of self-similar traffic and the quantification of the network resources to allocate in each resource renegotiation is non-trivial.
A number of dynamic bandwidth allocation methods are known, see U.S. Pat. Nos. 6,118,791 “Adaptive bandwidth allocation method for non-reserved traffic in a high-speed data transmission network, and system for implementing said method,” 5,991,308 “Lower overhead method for data transmission using ATM and SCDMA over hybrid fiber coax cable plant,” and 5,745,837 “Apparatus and method for digital data transmission over a CATV system using an ATM transport protocol and SCDMA.”, also see S. Chong, S. Li, J. Ghosh, “Predictive Dynamic Bandwidth Allocation for Efficient Transport of Real Time VBR Video over ATM,” IEEE Journal on Selected Areas in Comm, V:13, N:1, January 1995, pp. 12–23.
Typically, a predication is made, and a new allocation is based on the prediction and previous updates, see Chong, S. Li, J. Ghosh, “Efficient Transport of real time VBR Video over ATM via Dynamic Bandwidth Allocation,” University Of Texas at Austin, Austin, Tex. 78712, August 1995. The prediction can consider the overall, previous, or average bit rates, and buffer sizes, or combinations thereof. Peak-rate based methods result in a minimum number of updates. However, bandwidth is used inefficiently. Methods based on previous and average bit rates may not be able to match rapid changes in bit rates, causing delays.
Predicting exact bandwidth requirements in a network is a difficult problem. Clearly, the total bandwidth allocated during a session must at least match the total amount of data to be transmitted. If less than the required bandwidth is allocated, then some of the data must at least be delayed, or possibly irretrievably lost. If more than the required bandwidth is allocated, network resources are wasted. Therefore, it is desired to accurately predict traffic characteristics, and to dynamically allocate matching network resources accordingly.
Minimization of the number of renegotiations is also an important problem. Increasing the frequency of bandwidth renegotiations increases, and accordingly overload the network's signaling components. On the other hand, an inadequate number of renegotiations makes it difficult to follow traffic trends, and results in inefficient bandwidth utilization.
Setting the inter-negotiation times at fixed intervals (synchronous) is simple but not efficient. In asynchronous process, the bandwidth is adapted if and only if the demand exceeds a pre-assigned level. Traffic based renegotiation such as that introduced in the prior art, see Zhang et al., “RED-VBR: A new approach to support delay-sensitive VBR video in packet-switched networks,” Proc. NOSSDAV, pp. 258–272 1995, is asynchronous and is able to capture the near future bandwidth demand closely. However, a single very small or large video frame might cause high underutilization or over-utilization of the capacity for some time. The asynchronous operation can significantly reduce the adaptation frequency at the cost of decrease in utilization.
S. Chong, S. Li, J. Ghosh, “Predictive Dynamic Bandwidth Allocation for Efficient Transport of Real Time VBR Video over ATM,” IEEE Journal on Selected Areas in Comm, V:13, N:1, pp. 12–23, 1995, measures video traffic statistics in the frequency domain. They low pass filter the incoming traffic trace to capture the slow time variation of consecutive scene changes. However, they do not take high frequency components into account that can also demand non-negligible bandwidth.
Therefore, there is a need for improved generic method and system to dynamically allocate network resources to an applications traffic at asynchronously computed renegotiation times and with consideration of signal features in different frequency sub-bands.